According to a canned statement, its platform offers non-experts the ability to query their company's databases through “simple conversational style search”.

Francois Ajenstat, chief product officer at Tableau, said the smaller firm’s aim to offer a consumer-style experience was a natural fit with the Seattle business’ approach - which pushes the idea of “democratising” data.

ClearGraph's focus on using natural language queries for business data will appeal to Tableau’s existing customers, with Ajenstat saying the initial idea was to use the new tech to boost the number of Tableau users in a single organisation.

The deal - for an undisclosed amount - aims to speed up Tableau's use of natural language query, which Ajenstat said wasn’t being used much because the language people had to use “wasn’t that natural”.

“If you were to ask, ‘What are the most expensive homes in London?’, there’s a lot of meaning in that. [The system] has to understand it’s sale price and that it’s above a certain threshold," he said.

"Most natural language systems wouldn’t know how to handle that; you’d have to say ‘What are the homes in London that have an average sales price above a certain amount of money’, which isn’t very natural.”

The idea of ClearGraph’s technology - which it describes as patent-pending - is to cut out training and allow users to think less about how the data is stored before asking their question.

The firm says its platform will extract data from a number of disparate operational data stores and unify them in a single analytical warehouse. Once integrated, data flows are constantly updated through high-throughput JSON API or scheduled synchronisation events.

Ajenstat said it was too soon to offer a timeline for when Tableau would be offering ClearGraph’s products, but that it would go to market “as soon as we can” after the teams are integrated - ClearGraph’s five employees are moving over to Tableau as part of the deal.

The acquisition is only the third Tableau has ever made - in 2015, it picked up mobile graphics biz InfoActive and in 2016, the university spin-out Hyper - and Ajenstat stressed that further buy-outs were “not a core strategy” for the company.

The aim, he said, was to expand the platform over time, with continued investments in data governance and data preparation - the company’s aim is to offer end-to-end analytics.

Upcoming pre-release programs expected this year include Tableau’s Maestro project, which aims to speed up the time-consuming steps of data prep, and in-memory data engine Hyper, which aims to speed up analysis.

Earlier this month, the firm reported a 7 per cent growth in revenue for the quarter ending June 30, to $212.9m. It also saw a slight shrinkage in its net loss, which was $42.5m – compared with $47.5m in Q2 of 2016.